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199 datasets for “machine learning”

  1. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 12 Feb 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

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  2. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 5 Mar 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

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  3. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 16 Mar 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

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  4. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 29 Mar 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

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  5. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 4 Apr 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

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    • HTML
  6. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 10 Apr 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

    • PDF
    • HTML
  7. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 16 Apr 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

    • PDF
    • HTML
  8. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 5 May 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

    • PDF
    • HTML
  9. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 5 Jun 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

    • PDF
    • HTML
  10. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 17 Jun 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

    • PDF
    • HTML
  11. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 23 Jun 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

    • PDF
    • HTML
  12. data.gov.au

    Predicting Seabed Mud Content across the Australian Margin: Performance of Machine Learning Methods and their combinations with Ordinary Kriging and Inverse Distance Squared

    Australian Ocean Data NetworkUpdated 27 Jun 2026

    … In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK …

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    • HTML
  13. Open Government Canada

    CCDR: Volume 46-6 -June 2020: Artificial intelligence in public health

    Public Health Agency of Canada | Agence de la santé publique du CanadaUpdated 5 Jun 2020

    The Canada Communicable Disease Report is a bilingual, open-access, peer-reviewed journal on the prevention and control …

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  14. Data.gov Catalog

    EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog Using Transfer-Learning Aided Double-Difference Tomography

    Oak Ridge National LaboratoryUpdated 17 Feb 2025

    … V., Schoenball, M., and EGS Collab Team, 2020, Automatic Seismic Phase Picking Using Deep Learning for the EGS …

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  15. Data.gov Catalog

    Utah FORGE: Phase-Picking Based Microseismic Event Catalog - April 2024 Stimulation

    University Of UtahUpdated 23 Feb 2026

    This catalog contains microseismic event locations recorded during the April 2024 stimulation at the Utah FORGE site. Events …

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  16. Data.gov Catalog

    Utah FORGE 2-2439v2: A Multi-Component Approach to Characterizing In-Situ Stress - Final Report

    University of PittsburghUpdated 22 Dec 2025

    … at the Utah FORGE EGS site that integrates Machine Learning (ML) methods for predicting near-well principal stresses …

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  17. Data.gov Catalog

    The National Artificial Intelligence Research and Development Strategic Plan: 2019 Update

    NCO NITRDUpdated 20 Nov 2018

    Artificial intelligence (AI) holds tremendous promise to benefit nearly all aspects of society, including the economy, healthcare, security …

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  18. Data.gov Catalog

    Aboveground Biomass Estimates for Salt Marsh for the Contiguous United States, 2020

    ORNL_DAACUpdated 5 Nov 2026

    … Estimates were generated by XGBoost machine learning regression. Salt marsh extent was classified using an ensemble of XGBoost …

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  19. data.gov.au

    Building a Better Geochemical Picture of the Australian Landscape

    Geoscience Australia DataUpdated 16 Oct 2025

    … Levelled samples were used to train a machine learning algorithm (RandomForests) to generate a suite of predictive geochemical …

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  20. data.gov.au

    Revised weathering intensity model of Australia

    Geoscience Australia DataUpdated 16 Oct 2025

    … Here, I use a random forest decision tree machine learning algorithm to first establish a relationship between field …

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“machine learning” datasets · Open Data Finder